Long-term field comparison of the performances of multiple low-cost particulate matter sensors in an urban area

Exposure to ambient particulate matter (PM) air pollution is a leading risk factor contributing to morbidity and mortality, associated with 8.9 million deaths/year worldwide.  However, measurement of personal exposure to PM is hindered by poor spatial resolution of PM monitoring networks.  Low-cost PM sensors offer the potential to improve monitoring resolution in a cost-effective manner, but there are doubts over their reliability.  PM sensor boxes were constructed using low-cost PM micro-sensors from three different manufacturers.  Three boxes were deployed at each of two schools in Southampton, UK, for a seven month period, and sensor performance was analysed. Sensors appear to have different methods of determining concentration of PM size fractions, while comparison of sensor readings with readings from a nearby background station obtained Pearson coefficients up to 0.88 and indicated that low-cost sensors are sensitive to variations in relative humidity and temperature, although there was no obvious drift in performance over time.  Furthermore, sensor data was less correlated at lower pollution concentrations, which may have implications for their potential use in different locations.  This study indicates that, with appropriate consideration of potential confounding factors, low-cost PM sensors may be suitable for PM monitoring where reference-standard equipment is not available.

This dataset contains:

1. sensor_data.Rds (R format) containing the data from the sensors averaged (median) per 30 second over the period of the study
2. winddata.csv containing the data from the meteorological station over the period of the study
3. humidity_temperature_from_boxes.Rds containing the relative humidity and temperature recorded by the air quality monitors over the period of the study.